Author:

Keywords:

tactile sensing, shape recognition, neural networks, pattern classification, Science & Technology, Technology, Engineering, Electrical & Electronic, Instruments & Instrumentation, Engineering, 0906 Electrical and Electronic Engineering, 0912 Materials Engineering, 0913 Mechanical Engineering, Nanoscience & Nanotechnology, 4008 Electrical engineering, 4009 Electronics, sensors and digital hardware, 4017 Mechanical engineering

Abstract:

A direct, featureless process to classify contact impressions of objects gripped by a robot hand is presented. The information about the type of contact allows the selection of the most appropriate manipulating strategy to handle the grasped object. A learning vector quantization (LVQ) network is applied introducing a contact-pattern preprocessing technique to improve the robustness of the classification with respect to the pattern variations in position, orientation and size.